Alonso et al. [1]} proposed an event camera-based semantic segmentation method.
The event camera detects pixel information when the brightness changes, such as when the subject moves.
They do not capture personal information more clearly than the RGB cameras because event cameras only capture changes in intensities on a pixel-by-pixel basis.
In [1]}, event information from event cameras was formed as 6-channel images.
The first two channels were histograms of positive and negative events, whereas the other four channels were the mean and standard deviation of normalized timestamps at each pixel for the positive and negative events.
They showed that an Xception-based encoder–decoder architecture could learn semantic segmentation from the 6-channel information.
Although this method achieves semantic segmentation from privacy-preserved event cameras, it is difficult to detect people who are not moving.
